Course information: UCB On-Line Course Catalog and Schedule of Classes
Advances in networked embedded computing and communication devices have fueled the need for design techniques that can guarantee safety and performance specifications of embedded systems, or systems that involve the integration of discrete logic with the analog physical environment. Hybrid dynamical systems are continuous time, continuous variable systems with a phased operation. The phases of operation capture the system's discrete event or linguistic behavior, while the continuous variable dynamics capture the system's detailed or ``lower-level'' behavior. The two behaviors influence each other. Hierarchical organization is implicit in hybrid systems, since the discrete event dynamics represent planning which is based on an abstraction of the continuous dynamics. Hybrid systems are important in applications in real-time software, robotics and automation, mechatronics, aeronautics, air and ground transportation systems, systems biology, process control, and have recently been at the center of intense research activity in the control theory, computer-aided verification, and artificial intelligence communities. In the past several years, methodologies have been developed to model hybrid systems, to analyze their behavior, and to synthesize controllers that guarantee closed-loop safety and performance specifications. This class presents recent advances in the theory for analysis, control, verification, and simulation of hybrid dynamical systems, and shows the application of the theory to the design of the control architecture for complex, large scale systems.
We will present hybrid automaton models and related modeling approaches. In hybrid controller synthesis, we will treat different control system setups such as game theoretic and optimal control, switched systems, and other recent advances. For hybrid verification we treat decidability of timed automata, rectangular automata, general nonlinear systems with some approximation properties and some software verification tools. We present emerging approaches for hybrid system simulation. Finally, we apply the theory in case studies to complex problems such as automated highway systems, air traffic management systems, networks of unmanned vehicles, closing the loop around sensor networks, and systems biology.
Background in systems and control, such as EECS 221A or ME 232 is desirable. EECS 222 is offered concurrently and is a useful class to take with this one.
There is no required textbook. We will provide some lecture notes throughout the term. Additionally, the draft of a monograph by Lygeros, Tomlin and Sastry is available here:
Please sign the handout sheet on the first day of lectures (Tuesday January 16), OR email Tomlin, so that your email will be added to the class mailing list.Updated 01/11/17